IEEE - Institute of Electrical and Electronics Engineers, Inc. - Unsupervised Anomaly Detection With LSTM Neural Networks

Author(s): Tolga Ergen ; Suleyman Serdar Kozat
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Volume: PP
Page(s): 1 - 15
ISSN (Electronic): 2162-2388
ISSN (Paper): 2162-237X
DOI: 10.1109/TNNLS.2019.2935975
Regular:

We investigate anomaly detection in an unsupervised framework and introduce long short-term memory (LSTM) neural network-based algorithms. In particular, given variable length data sequences, we... View More

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